EP3234647B1 - Pixel based dead time correction - Google Patents
Pixel based dead time correction Download PDFInfo
- Publication number
- EP3234647B1 EP3234647B1 EP15816536.5A EP15816536A EP3234647B1 EP 3234647 B1 EP3234647 B1 EP 3234647B1 EP 15816536 A EP15816536 A EP 15816536A EP 3234647 B1 EP3234647 B1 EP 3234647B1
- Authority
- EP
- European Patent Office
- Prior art keywords
- dead time
- detector
- singles
- lor
- rate
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012937 correction Methods 0.000 title claims description 41
- 238000002600 positron emission tomography Methods 0.000 claims description 31
- 238000003384 imaging method Methods 0.000 claims description 27
- 238000000034 method Methods 0.000 claims description 27
- 238000012545 processing Methods 0.000 claims description 22
- 230000005855 radiation Effects 0.000 claims description 16
- 230000004044 response Effects 0.000 claims description 6
- 238000012879 PET imaging Methods 0.000 claims description 5
- 230000001131 transforming effect Effects 0.000 claims 2
- 238000001514 detection method Methods 0.000 description 11
- 238000011088 calibration curve Methods 0.000 description 7
- 238000004445 quantitative analysis Methods 0.000 description 7
- 230000000694 effects Effects 0.000 description 6
- 206010033799 Paralysis Diseases 0.000 description 5
- 230000003111 delayed effect Effects 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 239000002245 particle Substances 0.000 description 5
- 230000008901 benefit Effects 0.000 description 4
- 239000012217 radiopharmaceutical Substances 0.000 description 4
- 229940121896 radiopharmaceutical Drugs 0.000 description 4
- 230000002799 radiopharmaceutical effect Effects 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 230000000875 corresponding effect Effects 0.000 description 3
- 239000013078 crystal Substances 0.000 description 3
- 238000002059 diagnostic imaging Methods 0.000 description 3
- 230000005251 gamma ray Effects 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 238000005457 optimization Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000004075 alteration Effects 0.000 description 2
- 238000013459 approach Methods 0.000 description 2
- 230000002596 correlated effect Effects 0.000 description 2
- 230000007423 decrease Effects 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 238000012636 positron electron tomography Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 230000001276 controlling effect Effects 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000010191 image analysis Methods 0.000 description 1
- 239000012216 imaging agent Substances 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012633 nuclear imaging Methods 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 230000005258 radioactive decay Effects 0.000 description 1
- 229910052710 silicon Inorganic materials 0.000 description 1
- 239000010703 silicon Substances 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
- G01T1/16—Measuring radiation intensity
- G01T1/24—Measuring radiation intensity with semiconductor detectors
- G01T1/249—Measuring radiation intensity with semiconductor detectors specially adapted for use in SPECT or PET
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
- G01T1/16—Measuring radiation intensity
- G01T1/17—Circuit arrangements not adapted to a particular type of detector
- G01T1/171—Compensation of dead-time counting losses
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
- G01T1/29—Measurement performed on radiation beams, e.g. position or section of the beam; Measurement of spatial distribution of radiation
- G01T1/2914—Measurement of spatial distribution of radiation
- G01T1/2985—In depth localisation, e.g. using positron emitters; Tomographic imaging (longitudinal and transverse section imaging; apparatus for radiation diagnosis sequentially in different planes, steroscopic radiation diagnosis)
Definitions
- PET positron emission tomography
- PET quantitative analysis techniques seek to quantitatively assess the tissue radioactivity concentration, typically scaled by the injected activity per unit mass or another normalization factor.
- the quantitative analysis is based upon a linear relationship of patient image intensity with uptake of the imaging agent.
- F18 fluoride-18
- the most common quantitative image analysis metric is Standardized Uptake Value (SUV), which is calculated either pixel-wise yielding a parametric image, or over a Region of Interest (ROI).
- SUV Standardized Uptake Value
- ROI Region of Interest
- the linear relationship used to transform image intensity to tissue radioactivity concentration is derived from a SUV calibration which is typically computed as a single curve for the entire system, i.e. the same SUV calibration curve is used for each detector pixel.
- the SUV calibration curve also incorporates pixel dead time.
- the PET system typically operates near or in the so-called "paralyzed detector” regime, in which detector dead time is a significant factor.
- This dead time results because there is minimum time between gamma particle detection events - that is, if two gamma events impinge on the detector in (too) short succession, then the second event will not be detected because the detector has not yet reset after detecting the first event.
- the dead time is assumed to be the same for all pixels. In the SUV calibration curve, the dead time is seen as a sub-linearity to the singles rate-versus-radioactivity curve due to reduced observed counts at high radioactivity level caused by "missed" counts during the dead time.
- SUV calibration typically employs a cylinder source which contains F18 at a high activity level.
- the calibration source is located at the gantry ISO center, and parallel to patient bed (i.e. cylinder axis oriented along the axial direction). PET data acquisition is performed periodically, until the source is decayed to a level below detection.
- the reason for placing the cylinder source at the ISO centre is to factor out the variations caused by positioning and source unevenness.
- the radioactivity concentration of the calibration source is known as a function of time throughout the decay process, the result is the desired curve relating image intensity to radioactivity level. This process is known as SUV calibration.
- the SUV calibration uses a uniform cylinder phantom, with detectors at locations A, B, and C getting the same amount of exposure and having the same singles count rate. However, during a patient scan, detectors at A and B receive more exposure than the detectors at C, thus their singles rates are different.
- US 2009/072154 A1 discloses a method for reducing randoms variance in a Positron Emission Tomograph (PET) or Positron Emission Tomograph combined with another Medical Imaging device.
- An average of an element of the randoms event (delayeds) sinogram may be estimated by dividing fan sums in delayeds sinogram by singles rates taken from headers of the delayeds sinogram.
- the invention is defined by a positron emission tomography system according to claim 1, a method for computing a dead time correction factor per pixel according to claim 5 and a non-transitory computer readable medium according to claim 10. Further embodiments are defined by the dependent claims.
- One advantage resides in a dead time correction factor for each pixel in the system.
- Another advantage resides in linking pixel singles rates to dead time correction factors.
- the invention may take form in various components and arrangements of components, and in various steps and arrangements of steps.
- the drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention.
- Calibration techniques disclosed herein overcomes the problems described above by providing a complete map of dead time corrections for each detector pixel derived from signal measurement.
- the original SUV calibration technique remains the same, but is extended by obtaining the mapping of detector elements' live time (or dead time, which contains the same information as live time).
- the disclosed techniques determine random events, which are estimated using delayed events, and the link between detector element singles rate, radioactivity, live time, and dead-time correction is established.
- a positron emission tomography (PET) imaging system 10 is to be calibrated for quantitative analysis, such as SUV.
- the calibration technique uses a conventional calibration source 14 placed within an imaging region 16 (or bore) of a PET scanner 10.
- the illustrative PET scanner 10 further includes a patient bed or support 18 via which a patient is loaded into the examination region 16 (not used during the calibration procedure), and one or more PET detector rings 20.
- the calibration source 14 is as described previously with reference to the left diagram of FIGURE 1 , i.e. a cylinder source containing F18 at a high activity level located at the gantry ISO center (that is, equidistant from all detectors of a PET detector ring), and parallel to the patient bed 18 (i.e.
- a calibration processor 24 performs the SUV calibration including per-pixel dead time correction to generate an SUV calibration including dead time 26 .
- the calibration including dead time correction disclosed herein advantageously leverages coincidence-based data processing machinery that is used during patient (or, more generally, subject) imaging. Accordingly, subject imaging is first described.
- each detected gamma photon event is time stamped by a clock 30.
- each event is typically time stamped on circuitry that supports the SiPM.
- a coincident pair detector 34 compares the timestamps of the detected events to determine pairs of events which define the end points and/or, e.g. occur within a preselected coincidences time window.
- the ring of radiation detectors 20 (including crystals, (e.g., thousands) light detectors (e.g., hundreds, thousands), and support circuitry modules (e.g., tens)) are arranged around the imaging region 16 to detect radiation events (e.g., gamma rays) emitted from within the imaging region 16.
- the plurality of detectors 20 can be arranged in a plurality of modules 22, each of which sends digital signals indicative of at least energy and the time of each event.
- the scanner 10 further includes the support mechanism 18 for positioning a patient or an imaging subject in the imaging region 16 .
- the support mechanism 18 is linearly movable in an axial direction generally transverse to the PET ring or rings 20 to position the region of interest of the patient in the field of view, and in some imaging techniques to facilitate acquiring three dimensional imaging data.
- a suitable radiopharmaceutical is administered to the subject that will be scanned, and the subject is positioned within the imaging region 16.
- the radiopharmaceutical includes radioisotopes that undergo radioactive decay, which results in an emission of positrons. Each positron interacts with a nearby electron and annihilates, which produces two oppositely directed (180 degree) gamma rays having energies of about 511 keV each. The two oppositely directed gamma rays may strike opposing detectors at substantially the same time, i.e., coincidently.
- the pair detector 34 identifies pairs of substantially simultaneous or coincident gamma ray detections belonging to corresponding electron-positron annihilation events.
- This processing can include, for example, energy windowing (e.g., discarding radiation detection events outside of a selected energy window disposed about 511 keV) and coincidence-detecting circuitry (e.g., discarding radiation detection event pairs temporally separated from each other by greater than a selected time-window).
- a line of response (LOR) processor 36 processes the pair of events to identify a spatial LOR connecting the two gamma ray detections. Since the two gamma rays emitted by a positron-electron annihilation event are oppositely spatially directed, the electron-positron annihilation event is known to have occurred somewhere on the LOR.
- the detectors and the time stamping of the clock 30 have sufficiently high temporal resolution to detect a time-of-flight (TOF) difference between the two substantially simultaneous gamma ray detections.
- TOF time-of-flight
- a TOF processor 38 analyzes the time difference between the times of each event of the coincident pair to localize the positron-electron annihilation event along the LOR.
- a reconstruction engine 40 reconstructs an imaging data set comprising LOR (optionally with TOF localization) into images that are stored in storage or memory 42, and can be displayed, printed, archived, filmed, processed, transferred to another device, displayed on a monitor 44, etc.
- a radiologist or other suitable clinician can use the raw data and/or reconstructed image to control the TOF-PET scanner 10, diagnose the subject, etc.
- an SUV analysis module 50 applies the SUV calibration 26 generated by the calibration processor 24 to convert image intensity values to normalized tissue radioactivity concentration values so as to generate SUV data. If SUV is computed on a per-pixel basis, then an SUV image results, which can be displayed on the monitor 44. Alternatively, SUV can be computed for a region of interest (ROI) and presented as a numerical value for the ROI, again suitably displayed on the monitor 44. As disclosed herein, the SUV calibration 26 included dead time correction on a per-pixel basis.
- the term "detector pixel” denotes a detector image element of the PET ring 20 that is capable of detecting a single event.
- processing described above as well as other processing can be performed by one or more processing components.
- processing described herein can be processed by a single processing component, individual processing components, different combinations of processing components, and/or a combination thereof.
- the processing performed by the calibration processor 24 to generate the SUV calibration 26 is described.
- This calibration processing leverages the coincidence-based data processing machinery 34, 36 used during imaging.
- the singles rate is estimated for each pixel based on a randoms rate measured using the pair detector 34 with an applied time offset 54 as described herein.
- the singles rate for each pixel is then used to estimate the dead time for that pixel.
- the cylindrical phantom 14 is placed in the scanner 10 at the isocenter with its cylinder axis oriented horizontally, i.e. along the axial direction and transverse to the plane of the PET ring 20.
- the cylinder source contains a radiopharmaceutical, e.g. F18, at a high radioactivity level that is assessed as it decays for true coincidences, random events, and singles rate.
- a single is any 511 keV event that is detected by a detector 20, including true coincident events and random events and scatter events.
- a true coincidence event consists of two 511 keV particles detected within the coincidence time window, from which it may be inferred that both 511 keV particles were produced by a single electron-proton annihilation event.
- a random event consists of two 511 keV particles (or particles falling within the energy window for 511 keV) that are detected within the coincidence time window, but which do not in fact originate from a single electron-proton annihilation event
- a random occurring within the coincidence time window cannot be distinguished from a true coincidence event.
- the random rate can be measured using the following rationale. Since the two events making up the random are statistically independent (e.g. not sourced from a common electron-proton annihilation event), it follows that the rate of occurrence of such event pairs should be independent of the time interval separating them. To quantify, denote the coincidence window as ⁇ t , and two singles s 1 , s 2 occurring at times t 1 , t 2 respectively. Further define an offset time T. Then a randoms rate is defined as the rate of single pairs s 1 , s 2 for which t 2 - T lies within the coincidence window ⁇ t of the time t 1 .
- the offset T is selected to be large enough to exclude true coincidence events - in other words, there should be no overlap between the coincidence window ⁇ t and the offset window T + ⁇ t .
- the offset rate (that is, the rate of events s 1 , s 2 occurring at respective times t 1 , t 2 where t 2 - T lies within the coincidence window ⁇ t of the time t 1 ) should equal the randoms rate.
- the randoms rate can then be measured by imposing a time offset 54 (previously denoted as offset T ) on the pair detector 34, so that the coincidence detection machinery 34 is leveraged to measure the randoms rate.
- a listmode acquisition of the phantom 14 is performed by the PET scanner 10 to acquire listmode data for calibrating the PET scanner 10, in particular the detectors 20.
- the calibration source 14 is located at the gantry ISO centre, parallel to patient bed to factor out detector variations.
- the listmode acquisition is performed periodically, until the calibration source is decayed to a level such that the apparent dead time is zero.
- the detectors 20 are typically paralyzable detectors where a single event occurring at the detector during dead time restarts the dead time period.
- the apparent dead time is directly correlated to the singles rate of the detector 20, i.e. the pixel or crystal.
- the main output of a PET system is true coincidence events.
- the singles rates for each detector 20, i.e. pixel or crystal are not available and not easily obtained in the hardware data chain.
- the singles rate may be measured at the module level as a type of "dark current" metric for measuring performance of the detector module 22. In practice, however, both singles and random events have a local spatial variance across the pixel pairs.
- the rate of random events is proportional to the square of the singles rate, i.e., the singles rate of each detection element, and in turn correlated to the detector dead time.
- the singles rate can be estimated with a proper signal decomposition method.
- the calibration processor 24 determines the relationship of a singles rate to radioactivity of the radiopharmaceutical through direct measurement of the singles rate during the SUV calibration. With reference to FIGURE 3 , the calibration processor 24 averages the acquired single rate during SUV calibration for the entire system and assigns the average value to each detector 20 which is plotted against the detector exposure, i.e. the radioactivity of the phantom.
- the plot is nearly linear, however, the slope decreases as the average singles rate increases, indicating a paralyzed state for the detector 20.
- this sub-linear slope is due to some singles events failing to be detected because they occur during the detector pixel dead time while it is resetting from detecting a previous singles event.
- the sub-linear relationship captured in the SUV calibration of FIGURE 3 conventionally provides the dead time correction - but it is a system-level correction, and cannot account for different dead times for different detector pixels.
- the relationship of singles rate to a measured dead time is a determined dead time correction factor measured during SUV calibration, e.g. by extracting the dead time as a metric of the sub-linearity of the data of FIGURE 3 .
- the dead time correction factor is plotted against the average singles rate per pixel (left side of the figure).
- the dead time correction factor is suitably implemented as a multiplier for the coincidence window to compensate for dead time due to random events paralyzing the detector 20.
- the calibration processor 24 calculates a live time factor from the dead time factor, or directly from the data of FIGURE 3 .
- the live time factor is a reciprocal to the dead time correction factor - whereas the dead time measures the fraction of time the detector pixel is inactive due to paralysis, the live time measures the fraction of time the detector is active, i.e. in a non-paralyzed state.
- the live time is an alternative (i.e. reciprocal) representation of the dead time, and when used in its broadest sense herein the term "dead time" encompasses its representation as a reciprocal, or live time, value.
- live time has a practical advantage over dead time in that the live time is a true probability-type value that ranges between zero and one. Live time can be viewed as the detector's 20 probability of data loss in processing additional data.
- the live time factor is calculated as a function of detector's 20 singles rate per pixel (right side of the figure).
- the left hand side of FIGURE 4 is the dead time correction factor vs. singles rate
- the right hand side of FIGURE 4 is the live time factor vs. singles rate. Both plots describe the same correction but in a reciprocal manner.
- the live time factor is 1, indicating the detector is able to capture all photons, i.e. non-paralyzed.
- the live time factor decreases. This means more single events, or counts, are not detected.
- FIGURES 3-4 The processing of FIGURES 3-4 is typically performed on a module level or system level, as the PET coincidence detector machinery 34, 36 is not utilized. This means that conventionally the SUV calibration cannot provide a per-detector pixel dead time.
- the random rate i.e. delay rate, which is measured as the rate of "coincidence" events with the time offset 54 for one pixel, is typically a square function of the singles rate, i.e. for a detector pixel pair i , j where detector pixel i has a (ground truth) singles rate S i and detector pixel j has a (ground truth) singles rate S j , the randoms rate R ij for the pixel pair i , j is R ij ⁇ S i ⁇ S j (where the symbol " ⁇ " is used in its conventional sense to denote a proportional relationship).
- the singles rate for all detection elements is consistent after accounting for normalization differences (due to the radial symmetry of the cylinder calibration source 14, and neglecting any pixel-to-pixel variations), and so the system singles rate averaged over the number of pixels can be taken as the per-detector pixel singles rate.
- Equation 1 forms a system of nonlinear equations with one equation for each detector pair i, j, where R ij are known random rate measurements from the SUV calibration and S i and S j are unknowns.
- the system of equations is heavily overdetermined since each pixel i can pair with a large number of other pixels j , and vice versa.
- the calibration processor 24 resolves the nonlinear system of equations using a global optimization method such as least squares minimization method or the like.
- the calibration processor solves the nonlinear system of equations by generating a 2D histogram 600, 602, 604 of the random events.
- the histogram 600, 602, 604 is a map of the singles rate with a scaling factor.
- S is the system singles rate (e.g. as provided in the calibration data of FIGURE 3 );
- the summation of all individual singles rates should be the same as the system singles rate S.
- the histogram 600, 602, 604 divided into a top half 606 and bottom half 608 of the ring of detectors 20 in the gantry. In this particular embodiment there are 6 total frames representing a part of the bed position of the entire scan of the body, where, in continuing reference to FIGURE 6 , histograms of frame 2 600, frame 4 602, and frame 6 604 , are shown.
- the intensity of each pixel corresponds to the singles rate derived from random events.
- the singles rate is represented as colors in the histogram.
- the singles rate is visually represented according to grey scale intensity. From the histograms 600, 602, 604, pixels with high singles rates varies from pixels with low singles rates by as much as 30%.
- the 2D histogram can be represented in a lookup table.
- the calibration processor 24 calculates the live time (LT) of two pixels i and j at the ends of each LOR.
- f ( S i ) is the live time factor corresponding to the singles rate S i read from the plot of FIGURE 4 .
- the determined dead time correction factor DT ij is used as a multiplier to the coincident window ⁇ t to correct the true coincidences rate for the dead time.
- the calibration processor 24 stores the dead time correction factor DT ij in the correction memory 26 as part of the SUV calibration for use by the system when performing SUV or other quantitative analysis of a patient image.
- a method for computing deadtime time correction factor per pixel is depicted.
- listmode data are acquired of the calibration phantom 14.
- a random rate is determined from the listmode data for each LOR by applying the pair detector 34 to the listmode data with the offset 54.
- a nonlinear system of random rate equations is generated in accord with Equation 1 and solved to generate a singles rate at each detector pixel.
- the nonlinear system is suitably solved using a 2D histogram or the like as described with reference to FIGURE 6 , or by a least squares optimization method, or so forth.
- a live time factor is computed for each LOR of a coincident pair using Equation 3.
- a dead time correction factor is computed as the reciprocal the live time for each LOR as per Equation 4.
- the SUV calibration of FIGURE 3 can be adjusted to remove the sub-linearity introduced by the dead time, since the dead time is now corrected separately, e.g. by scaling the coincidence window as DT ij ⁇ t .
- One way to do this is to fit the lower portion of the singles rate-vs.-radioactivity curve to a straight line, since dead time is negligible in this region of the SUV calibration.
- This linearized SUV calibration curve is suitably stored as part of the SUV calibration 26 (along with the data of FIGURE 4 or a parametric equation derived therefrom, e.g. function f , and optionally FIGURE 5 , or the scaling factor ⁇ extracted from this curve).
- the SUV analysis module 50 can apply the SUV calibration 26 as follows. Given a listmode imaging dataset for a subject, the randoms R ij for each LOR i, j is obtained by applying the pair detector 34 to the list mode data with the offset 54. Equation 1 is applied to generate a system of equations that are solved to determine the singles rates S i and S j for respective detector pixels i , j . Equation 3 is then applied (leveraging the calibration data of FIGURE 4 stored as part of the SUV calibration 26 as the function f ) to generate the live time LT ij for the LOR i, j. The dead time DT ij is then the reciprocal of this as per Equation 4. Thereafter, the list mode imaging data set is processed in the usual way, e.g.
- This image may be useful by itself, insofar as the image is made more accurate by eliminating the distorting effect of dead time.
- the image is processed by the linearized version of the SUV calibration curve (i.e. linearized version of FIGURE 3 , again stored as part of the SUV calibration 26 ) to convert intensity values to (normalized) activity or uptake levels.
- a memory includes any device or system storing data, such as a random access memory (RAM) or a read-only memory (ROM).
- RAM random access memory
- ROM read-only memory
- An electronic data processing device including a processor with suitable firmware or software implements the various processing components 24, 34, 36, 38, 40, 50.
- Such an electronic data processing device may comprise any device or system processing input data to produce output data, such as a microprocessor, a microcontroller, a graphic processing unit (GPU), an application-specific integrated circuit (ASIC), a FPGA, and the like; a controller includes any device or system controlling another device or system, and typically includes at least one processor; a user input device includes any device, such as a mouse or keyboard, allowing a technician of the user input device to provide input to another device or system; and a display device includes any device for displaying data, such as a liquid crystal display (LCD) or a light emitting diode (LED) display.
- LCD liquid crystal display
- LED light emitting diode
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- High Energy & Nuclear Physics (AREA)
- Molecular Biology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Nuclear Medicine (AREA)
- Measurement Of Radiation (AREA)
Description
- The following relates generally to medical imaging. It finds particular application in calibration of a positron emission tomography (PET) detectors for quantitative analysis, imaging, or other tasks, and will be described with particular reference thereto. However, it is to be understood that it also finds application in other usage scenarios and is not necessarily limited to the aforementioned application.
- PET quantitative analysis techniques seek to quantitatively assess the tissue radioactivity concentration, typically scaled by the injected activity per unit mass or another normalization factor. The quantitative analysis is based upon a linear relationship of patient image intensity with uptake of the imaging agent. For a fluoride-18 (F18) radioisotope, the most common quantitative image analysis metric is Standardized Uptake Value (SUV), which is calculated either pixel-wise yielding a parametric image, or over a Region of Interest (ROI). However, the linear relationship used to transform image intensity to tissue radioactivity concentration is derived from a SUV calibration which is typically computed as a single curve for the entire system, i.e. the same SUV calibration curve is used for each detector pixel. The SUV calibration curve also incorporates pixel dead time. During clinical imaging the PET system typically operates near or in the so-called "paralyzed detector" regime, in which detector dead time is a significant factor. This dead time results because there is minimum time between gamma particle detection events - that is, if two gamma events impinge on the detector in (too) short succession, then the second event will not be detected because the detector has not yet reset after detecting the first event. Because a single system-level SUV calibration curve is used, the dead time is assumed to be the same for all pixels. In the SUV calibration curve, the dead time is seen as a sub-linearity to the singles rate-versus-radioactivity curve due to reduced observed counts at high radioactivity level caused by "missed" counts during the dead time.
- SUV calibration typically employs a cylinder source which contains F18 at a high activity level. The calibration source is located at the gantry ISO center, and parallel to patient bed (i.e. cylinder axis oriented along the axial direction). PET data acquisition is performed periodically, until the source is decayed to a level below detection. The reason for placing the cylinder source at the ISO centre is to factor out the variations caused by positioning and source unevenness. As the radioactivity concentration of the calibration source is known as a function of time throughout the decay process, the result is the desired curve relating image intensity to radioactivity level. This process is known as SUV calibration.
- With reference to
FIGURE 1 , the difference between SUV calibration and patient scan is illustrated. The SUV calibration uses a uniform cylinder phantom, with detectors at locations A, B, and C getting the same amount of exposure and having the same singles count rate. However, during a patient scan, detectors at A and B receive more exposure than the detectors at C, thus their singles rates are different. - However, such detector pixel-level effects are not accounted for by the single system-level SUV calibration curve.
-
US 2009/072154 A1 discloses a method for reducing randoms variance in a Positron Emission Tomograph (PET) or Positron Emission Tomograph combined with another Medical Imaging device. An average of an element of the randoms event (delayeds) sinogram may be estimated by dividing fan sums in delayeds sinogram by singles rates taken from headers of the delayeds sinogram. - The article "Variance Reduction on Randoms from delayed coincidence histograms for the HRRT" by Larry G. Byars et al., IEEE Nuclear Science Symposium Conference, Piscataway, NJ, USA, October 2005, reports on a new algorithm for variance reduction on random coincidences (VRR) that has been validated for the HRRT. According to the authors, VRR is crucial to achieve quantitation for low statistics dynamic studies reconstructed with iterative methods based on ordinary Poisson model. On HRRT, VRR cannot be performed in projection space since individual LOR's are mixed after histogramming in parallel projection space using nearest neighbor approximation and axial compression. The proposed algorithm uses the classical random rate equation on the 4.5 · 109 LOR's.
- The invention is defined by a positron emission tomography system according to
claim 1, a method for computing a dead time correction factor per pixel according to claim 5 and a non-transitory computer readable medium according toclaim 10. Further embodiments are defined by the dependent claims. - It is preferred that the operation of determining a singles rate for each detector pixel comprises solving a system of equations Rij = 2τSi ∗ Sj , where Rij is the determined random rate of the LOR defined by detector pixels i and j; τ is the coincidence window width of the coincident 511 keV events detector of the PET imaging system; and Si and Sj are unknown singles rates for detector pixels i and j respectively, wherein solving the system of equations Rij = 2τSi ∗ Sj includes the at least one processor further configured to: perform a least squares optimization of the singles rate per detector pixel.
- One advantage resides in a dead time correction factor for each pixel in the system.
- Another advantage resides in linking pixel singles rates to dead time correction factors.
- Still further advantages of the present invention will be appreciated to those of ordinary skill in the art upon reading and understand the following detailed description
- The invention may take form in various components and arrangements of components, and in various steps and arrangements of steps. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention.
-
FIGURE 1 depicts differences between a cylindrical phantom and a patient. -
FIGURE 2 illustrates a nuclear imaging system to be calibrated. -
FIGURE 3 depicts a plot of average singles rate vs. radioactivity. -
FIGURE 4 depicts dead time correction factor vs. singles rate per pixel plot and a live time factor vs. singles rate per pixel plot. -
FIGURE 5 depicts an average singles rate per pixel vs. average random rate per pixel plot. -
FIGURE 6 depicts two-dimensional histograms of singles rates for different frames of the calibration source -
FIGURE 7 depicts a method for calibrating a diagnostic imaging system.. - Calibration techniques disclosed herein overcomes the problems described above by providing a complete map of dead time corrections for each detector pixel derived from signal measurement. Advantageously, the original SUV calibration technique remains the same, but is extended by obtaining the mapping of detector elements' live time (or dead time, which contains the same information as live time). For patient scans, the disclosed techniques determine random events, which are estimated using delayed events, and the link between detector element singles rate, radioactivity, live time, and dead-time correction is established.
- With reference to
FIGURE 2 , a positron emission tomography (PET)imaging system 10 is to be calibrated for quantitative analysis, such as SUV. The calibration technique uses aconventional calibration source 14 placed within an imaging region 16 (or bore) of aPET scanner 10. Theillustrative PET scanner 10 further includes a patient bed or support 18 via which a patient is loaded into the examination region 16 (not used during the calibration procedure), and one or morePET detector rings 20. Thecalibration source 14 is as described previously with reference to the left diagram ofFIGURE 1 , i.e. a cylinder source containing F18 at a high activity level located at the gantry ISO center (that is, equidistant from all detectors of a PET detector ring), and parallel to the patient bed 18 (i.e. cylinder axis oriented along the axial direction). Radiation events are detected by thePET detector rings 20 via scintillator and silicon photomultipliers (SiPMs) or other detectors such as photomultiplier tubes (PMT's), or avalanche photodiodes (APDs) or the like making up detector arrays of thePET rings 20. Acalibration processor 24 performs the SUV calibration including per-pixel dead time correction to generate an SUV calibration includingdead time 26. - The calibration including dead time correction disclosed herein advantageously leverages coincidence-based data processing machinery that is used during patient (or, more generally, subject) imaging. Accordingly, subject imaging is first described.
- During imaging, each detected gamma photon event is time stamped by a
clock 30. In a digital PET system each event is typically time stamped on circuitry that supports the SiPM. Acoincident pair detector 34 compares the timestamps of the detected events to determine pairs of events which define the end points and/or, e.g. occur within a preselected coincidences time window. - The ring of radiation detectors 20 (including crystals, (e.g., thousands) light detectors (e.g., hundreds, thousands), and support circuitry modules (e.g., tens)) are arranged around the
imaging region 16 to detect radiation events (e.g., gamma rays) emitted from within theimaging region 16. As depicted, the plurality ofdetectors 20 can be arranged in a plurality ofmodules 22, each of which sends digital signals indicative of at least energy and the time of each event. Thescanner 10 further includes the support mechanism 18 for positioning a patient or an imaging subject in theimaging region 16. In some instances, the support mechanism 18 is linearly movable in an axial direction generally transverse to the PET ring or rings 20 to position the region of interest of the patient in the field of view, and in some imaging techniques to facilitate acquiring three dimensional imaging data. - In preparation for imaging with the
scanner 10, a suitable radiopharmaceutical is administered to the subject that will be scanned, and the subject is positioned within theimaging region 16. The radiopharmaceutical includes radioisotopes that undergo radioactive decay, which results in an emission of positrons. Each positron interacts with a nearby electron and annihilates, which produces two oppositely directed (180 degree) gamma rays having energies of about 511 keV each. The two oppositely directed gamma rays may strike opposing detectors at substantially the same time, i.e., coincidently. - The
pair detector 34 identifies pairs of substantially simultaneous or coincident gamma ray detections belonging to corresponding electron-positron annihilation events. This processing can include, for example, energy windowing (e.g., discarding radiation detection events outside of a selected energy window disposed about 511 keV) and coincidence-detecting circuitry (e.g., discarding radiation detection event pairs temporally separated from each other by greater than a selected time-window). - Upon identifying an event pair, a line of response (LOR)
processor 36 processes the pair of events to identify a spatial LOR connecting the two gamma ray detections. Since the two gamma rays emitted by a positron-electron annihilation event are oppositely spatially directed, the electron-positron annihilation event is known to have occurred somewhere on the LOR. In TOF-PET, the detectors and the time stamping of theclock 30 have sufficiently high temporal resolution to detect a time-of-flight (TOF) difference between the two substantially simultaneous gamma ray detections. In such TOF PET imaging systems, aTOF processor 38 analyzes the time difference between the times of each event of the coincident pair to localize the positron-electron annihilation event along the LOR. - A
reconstruction engine 40 reconstructs an imaging data set comprising LOR (optionally with TOF localization) into images that are stored in storage ormemory 42, and can be displayed, printed, archived, filmed, processed, transferred to another device, displayed on amonitor 44, etc. A radiologist or other suitable clinician can use the raw data and/or reconstructed image to control the TOF-PET scanner 10, diagnose the subject, etc. - To perform quantitative analysis, such as illustrative Standardized Uptake Value (SUV) analysis, an
SUV analysis module 50 applies theSUV calibration 26 generated by thecalibration processor 24 to convert image intensity values to normalized tissue radioactivity concentration values so as to generate SUV data. If SUV is computed on a per-pixel basis, then an SUV image results, which can be displayed on themonitor 44. Alternatively, SUV can be computed for a region of interest (ROI) and presented as a numerical value for the ROI, again suitably displayed on themonitor 44. As disclosed herein, theSUV calibration 26 included dead time correction on a per-pixel basis. As used herein, the term "detector pixel" denotes a detector image element of thePET ring 20 that is capable of detecting a single event. - It is to be appreciated that the processing described above as well as other processing can be performed by one or more processing components. Thus, the processing described herein can be processed by a single processing component, individual processing components, different combinations of processing components, and/or a combination thereof.
- Having described subject imaging, the processing performed by the
calibration processor 24 to generate theSUV calibration 26 is described. This calibration processing leverages the coincidence-baseddata processing machinery pair detector 34 with an applied time offset 54 as described herein. The singles rate for each pixel is then used to estimate the dead time for that pixel. - To perform the calibration, the
cylindrical phantom 14 is placed in thescanner 10 at the isocenter with its cylinder axis oriented horizontally, i.e. along the axial direction and transverse to the plane of thePET ring 20. The cylinder source contains a radiopharmaceutical, e.g. F18, at a high radioactivity level that is assessed as it decays for true coincidences, random events, and singles rate. A single is any 511 keV event that is detected by adetector 20, including true coincident events and random events and scatter events. A true coincidence event consists of two 511 keV particles detected within the coincidence time window, from which it may be inferred that both 511 keV particles were produced by a single electron-proton annihilation event. A random event consists of two 511 keV particles (or particles falling within the energy window for 511 keV) that are detected within the coincidence time window, but which do not in fact originate from a single electron-proton annihilation event. - A random occurring within the coincidence time window cannot be distinguished from a true coincidence event. However, it is recognized herein that the random rate can be measured using the following rationale. Since the two events making up the random are statistically independent (e.g. not sourced from a common electron-proton annihilation event), it follows that the rate of occurrence of such event pairs should be independent of the time interval separating them. To quantify, denote the coincidence window as Δt, and two singles s 1, s 2 occurring at times t 1, t 2 respectively. Further define an offset time T. Then a randoms rate is defined as the rate of single pairs s 1, s 2 for which t 2 - T lies within the coincidence window Δt of the time t 1. In this estimate, the offset T is selected to be large enough to exclude true coincidence events - in other words, there should be no overlap between the coincidence window Δt and the offset window T + Δt. Because randoms are statistically independent, the offset rate (that is, the rate of events s 1, s 2 occurring at respective times t1 , t 2 where t 2 - T lies within the coincidence window Δt of the time t 1) should equal the randoms rate.
- In view of the foregoing, the randoms rate can then be measured by imposing a time offset 54 (previously denoted as offset T) on the
pair detector 34, so that thecoincidence detection machinery 34 is leveraged to measure the randoms rate. - To perform the calibration, a listmode acquisition of the
phantom 14 is performed by thePET scanner 10 to acquire listmode data for calibrating thePET scanner 10, in particular thedetectors 20. Thecalibration source 14 is located at the gantry ISO centre, parallel to patient bed to factor out detector variations. The listmode acquisition is performed periodically, until the calibration source is decayed to a level such that the apparent dead time is zero. - The
detectors 20 are typically paralyzable detectors where a single event occurring at the detector during dead time restarts the dead time period. The apparent dead time is directly correlated to the singles rate of thedetector 20, i.e. the pixel or crystal. However, the main output of a PET system is true coincidence events. Typically, the singles rates for eachdetector 20, i.e. pixel or crystal, are not available and not easily obtained in the hardware data chain. For example, the singles rate may be measured at the module level as a type of "dark current" metric for measuring performance of thedetector module 22. In practice, however, both singles and random events have a local spatial variance across the pixel pairs. The rate of random events is proportional to the square of the singles rate, i.e., the singles rate of each detection element, and in turn correlated to the detector dead time. As disclosed herein, using random events, which are readily available for each LOR, the singles rate can be estimated with a proper signal decomposition method. The random events rates are estimated as already described, using the delay technique which adds the time delay offset 54 to one of the coincidence paths, e.g., T =100 ns, such that "coincidence" events with this offset 54 are classified as random events and not true coincidence events, and the randoms rate is measured on a per-detector pixel pair basis using the same machinery that measures the coincidence rate. - With continuing reference to
FIGURE 2 and with further reference toFIGURE 3 , thecalibration processor 24 determines the relationship of a singles rate to radioactivity of the radiopharmaceutical through direct measurement of the singles rate during the SUV calibration. With reference toFIGURE 3 , thecalibration processor 24 averages the acquired single rate during SUV calibration for the entire system and assigns the average value to eachdetector 20 which is plotted against the detector exposure, i.e. the radioactivity of the phantom. The pixels of thedetector 20 are arranged in the gantry in a tangential direction x, about Nx = 576 detector elements, and an axial direction y, about Ny = 40 detector elements, resulting in 23,040, i.e. 576*40 or Ny*Ny, pixels in the system. With continuing reference toFIGURE 3 , the plot is nearly linear, however, the slope decreases as the average singles rate increases, indicating a paralyzed state for thedetector 20. Again, this sub-linear slope is due to some singles events failing to be detected because they occur during the detector pixel dead time while it is resetting from detecting a previous singles event. The sub-linear relationship captured in the SUV calibration ofFIGURE 3 conventionally provides the dead time correction - but it is a system-level correction, and cannot account for different dead times for different detector pixels. - The relationship of singles rate to a measured dead time is a determined dead time correction factor measured during SUV calibration, e.g. by extracting the dead time as a metric of the sub-linearity of the data of
FIGURE 3 . With reference toFIGURE 4 , the dead time correction factor is plotted against the average singles rate per pixel (left side of the figure). The dead time correction factor is suitably implemented as a multiplier for the coincidence window to compensate for dead time due to random events paralyzing thedetector 20. Additionally or alternatively, thecalibration processor 24 calculates a live time factor from the dead time factor, or directly from the data ofFIGURE 3 . The live time factor is a reciprocal to the dead time correction factor - whereas the dead time measures the fraction of time the detector pixel is inactive due to paralysis, the live time measures the fraction of time the detector is active, i.e. in a non-paralyzed state. Said another way, the live time is an alternative (i.e. reciprocal) representation of the dead time, and when used in its broadest sense herein the term "dead time" encompasses its representation as a reciprocal, or live time, value. As seen inFIGURE 4 , live time has a practical advantage over dead time in that the live time is a true probability-type value that ranges between zero and one. Live time can be viewed as the detector's 20 probability of data loss in processing additional data. The live time factor is calculated as a function of detector's 20 singles rate per pixel (right side of the figure). The left hand side ofFIGURE 4 is the dead time correction factor vs. singles rate, and the right hand side ofFIGURE 4 is the live time factor vs. singles rate. Both plots describe the same correction but in a reciprocal manner. At a lower singles rate, the live time factor is 1, indicating the detector is able to capture all photons, i.e. non-paralyzed. As the singles rate increases, the live time factor decreases. This means more single events, or counts, are not detected. - The processing of
FIGURES 3-4 is typically performed on a module level or system level, as the PETcoincidence detector machinery - With reference to
FIGURE 5 , the random rate, i.e. delay rate, which is measured as the rate of "coincidence" events with the time offset 54 for one pixel, is typically a square function of the singles rate, i.e. for a detector pixel pair i, j where detector pixel i has a (ground truth) singles rate Si and detector pixel j has a (ground truth) singles rate Sj , the randoms rate Rij for the pixel pair i, j is Rij ∝ Si × Sj (where the symbol "∝" is used in its conventional sense to denote a proportional relationship). In one embodiment, the singles rate for each detection element is used, computed using the relation Rij = 2τSiSj where τ is the coincidence window width and Rij is acquired for each pixel pair i, j using thecoincidence machinery cylinder calibration source 14, and neglecting any pixel-to-pixel variations), and so the system singles rate averaged over the number of pixels can be taken as the per-detector pixel singles rate. - In the following, the singles rate per-detector pixel computed from the randoms rates Rij is described in further detail. The measured random rate Rij , also referred to herein as the delay rate, between a detector pair i and j is related to the corresponding singles rate of each detector i and detector j according to:
Equation 1 forms a system of nonlinear equations with one equation for each detector pair i, j, where Rij are known random rate measurements from the SUV calibration and S i and S j are unknowns. The system of equations is heavily overdetermined since each pixel i can pair with a large number of other pixels j, and vice versa. In one embodiment, thecalibration processor 24 resolves the nonlinear system of equations using a global optimization method such as least squares minimization method or the like. -
- Where S is the system singles rate (e.g. as provided in the calibration data of
FIGURE 3 ); sxy is the singles rate derived from random events for a detector pixel in 2D space, where x=0,1,...Nx, and y=0,1,...Ny. The summation of all individual singles rates should be the same as the system singles rate S. Thehistogram top half 606 andbottom half 608 of the ring ofdetectors 20 in the gantry. In this particular embodiment there are 6 total frames representing a part of the bed position of the entire scan of the body, where, in continuing reference toFIGURE 6 , histograms offrame 2 600,frame 4 602, andframe 6 604, are shown. The intensity of each pixel corresponds to the singles rate derived from random events. In one embodiment, the singles rate is represented as colors in the histogram. In another embodiment, the singles rate is visually represented according to grey scale intensity. From thehistograms - To obtain dead time per pixel, the
calibration processor 24 calculates the live time (LT) of two pixels i and j at the ends of each LOR. Thecalibration processor 24 calculates the live time as a combination of the singles rates of each detector usingFIGURE 4 . The dead time correction factor is calculated as the inverse of the live time factor for the LOR depicted ascalibration processor 24 stores the dead time correction factor DTij in thecorrection memory 26 as part of the SUV calibration for use by the system when performing SUV or other quantitative analysis of a patient image. - With reference to
FIGURE 7 , to summarize, a method for computing deadtime time correction factor per pixel is depicted. At astep 702, listmode data are acquired of thecalibration phantom 14. At astep 704, a random rate is determined from the listmode data for each LOR by applying thepair detector 34 to the listmode data with the offset 54. At astep 706, a nonlinear system of random rate equations is generated in accord withEquation 1 and solved to generate a singles rate at each detector pixel. The nonlinear system is suitably solved using a 2D histogram or the like as described with reference toFIGURE 6 , or by a least squares optimization method, or so forth. At astep 708, a live time factor is computed for each LOR of a coincident pair using Equation 3. At astep 710, a dead time correction factor is computed as the reciprocal the live time for each LOR as perEquation 4. - The SUV calibration of
FIGURE 3 can be adjusted to remove the sub-linearity introduced by the dead time, since the dead time is now corrected separately, e.g. by scaling the coincidence window as DTij Δt. One way to do this is to fit the lower portion of the singles rate-vs.-radioactivity curve to a straight line, since dead time is negligible in this region of the SUV calibration. This linearized SUV calibration curve is suitably stored as part of the SUV calibration 26 (along with the data ofFIGURE 4 or a parametric equation derived therefrom, e.g. function f, and optionallyFIGURE 5 , or the scaling factor τ extracted from this curve). - The
SUV analysis module 50 can apply theSUV calibration 26 as follows. Given a listmode imaging dataset for a subject, the randoms Rij for each LOR i, j is obtained by applying thepair detector 34 to the list mode data with the offset 54.Equation 1 is applied to generate a system of equations that are solved to determine the singles rates Si and Sj for respective detector pixels i, j. Equation 3 is then applied (leveraging the calibration data ofFIGURE 4 stored as part of theSUV calibration 26 as the function f) to generate the live time LTij for the LOR i, j. The dead time DTij is then the reciprocal of this as perEquation 4. Thereafter, the list mode imaging data set is processed in the usual way, e.g. applying thecoincidence machinery reconstruction engine 40 to generate an image with dead time correction. This image may be useful by itself, insofar as the image is made more accurate by eliminating the distorting effect of dead time. If quantitative analysis is desired, the image is processed by the linearized version of the SUV calibration curve (i.e. linearized version ofFIGURE 3 , again stored as part of the SUV calibration 26) to convert intensity values to (normalized) activity or uptake levels. - As used herein, a memory includes any device or system storing data, such as a random access memory (RAM) or a read-only memory (ROM). An electronic data processing device including a processor with suitable firmware or software implements the
various processing components - The invention has been described with reference to the preferred embodiments. Modifications and alterations may occur to others upon reading and understanding the preceding detailed description. It is intended that the invention be construed as including all such modifications and alterations insofar as they come within the scope of the invention as defined by the appended claims.
Claims (10)
- A positron emission tomography (PET) system comprising:a plurality of radiation detectors (20) configured to detect coincident radiation event pairs defining lines of response (LORs) emanating from an imaging region and detected by detector pixels of the radiation detectors; andat least one processor configured to:cause the radiation detectors to acquire listmode data comprising singles events detected by the detector pixels; and characterized in thatthe at least one processor is further configured tocompute a dead time correction factor for each LOR defined by a pair of detector pixels,wherein the computing the dead time correction factor for each LOR includes:determining a random rate for each LOR from the listmode data;determining a singles rate for each detector pixel from the determined random rates; andcomputing a live time LTij factor for the LOR defined by detector pixels i and j based on the singles rates Si and Sj for the detector pixels i and j respectively.
- The system according to claim 1, wherein the operation of determining a singles rate for each detector pixel comprises solving a system of equations Rij ∝ Si ∗ Sj , where Rij is the determined random rate of the LOR defined by detector pixels i and j; the symbol "∝" denotes a proportional relationship; and Si and Sj are unknown singles rates for detector pixels i and j respectively.
- The system according to claim 2, wherein solving the system of equations Rij ∝ Si ∗ Sj includes the at least one processor further configured to:
generate a histogram map of the singles rate per pixel, wherein the histogram includes a scaling factor. - A method for computing a dead time correction factor per detector pixel in a positron emission tomography (PET) scanner, the method comprising:using PET radiation detectors, detecting a plurality of 511 keV radiation events emanating from an imaging region; andusing an electronic data processing device,and characterized in thatthe processing device is used for computing a dead time correction factor for each line of response (LOR) defined by a pair of detector pixels of the PET radiation detectors,wherein computing the dead time correction factor includes:determining a random rate for each LOR;determining a singles rate for each detector pixel of the PET radiation detectors from the determined random rates; andcomputing a live time factor LTij for the LOR defined by detector pixels i and j based on the singles rates Si and Sj for the detector pixels i and j respectively.
- The method according to claim 5, wherein the operation of determining a singles rate for each detector pixel comprises solving a system of equations Rij = 2τSi ∗ Sj , where Rij is the determined random rate of the LOR defined by detector pixels i and j; τ is a coincidence window width; and Si and Sj are unknown singles rates for detector pixels i and j respectively.
- The method according to claim 6, wherein solving the system of equations Rij = 2τSi ∗ Sj includes the at least one processor further configured to:
generating a histogram map of the singles rate per pixel, wherein the histogram includes a scaling factor. - The method according to any one of claims 5-8 wherein the detecting comprises acquiring PET imaging data for an imaging subject, and the method further comprises:using the electronic data processing device, reconstructing the PET imaging data to generate a PET image of the imaging subject and transforming the PET image to generate Standardized Uptake Value (SUV) data for the imaging subject comprising a parametric SUV image or an SUV value for a region of interest;wherein the reconstructing and transforming includes correcting the PET imaging data for detector dead time using the dead time correction factors for the LORs.
- A non-transitory computer readable medium carrying software for controlling one or more processors to perform the method steps of computing a dead time correction factor for each line of response (LOR) defined by a pair of detector pixels of PET radiation detectors of a PET scanner which are used for detecting a plurality of 511 keV radiation events emanating from an imaging region,
wherein computing the dead time correction factor includes:determining a random rate for each LOR; determining a singles rate for each detector pixel of the PET radiation detectors from the determined random rates; andcomputing a live time factor LTij for the LOR defined by detector pixels i and j based on the singles rates Si and Sj for the detector pixels i and j respectively.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201462091801P | 2014-12-15 | 2014-12-15 | |
PCT/IB2015/059594 WO2016097977A1 (en) | 2014-12-15 | 2015-12-14 | Pixel based dead time correction |
Publications (2)
Publication Number | Publication Date |
---|---|
EP3234647A1 EP3234647A1 (en) | 2017-10-25 |
EP3234647B1 true EP3234647B1 (en) | 2021-03-03 |
Family
ID=55024192
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP15816536.5A Active EP3234647B1 (en) | 2014-12-15 | 2015-12-14 | Pixel based dead time correction |
Country Status (5)
Country | Link |
---|---|
US (1) | US10101474B2 (en) |
EP (1) | EP3234647B1 (en) |
JP (1) | JP6464269B2 (en) |
CN (1) | CN107110983B (en) |
WO (1) | WO2016097977A1 (en) |
Families Citing this family (27)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8017915B2 (en) | 2008-03-14 | 2011-09-13 | Reflexion Medical, Inc. | Method and apparatus for emission guided radiation therapy |
JP6850482B2 (en) | 2015-06-10 | 2021-03-31 | リフレクション メディカル, インコーポレイテッド | High bandwidth binary multi-leaf collimator design |
WO2018093933A1 (en) | 2016-11-15 | 2018-05-24 | Reflexion Medical, Inc. | System for emission-guided high-energy photon delivery |
CN110248604B (en) | 2016-11-15 | 2023-07-21 | 反射医疗公司 | Radiotherapy patient platform |
CN108109182B (en) * | 2016-11-24 | 2021-08-24 | 上海东软医疗科技有限公司 | PET image reconstruction method and device |
WO2018183748A1 (en) | 2017-03-30 | 2018-10-04 | Reflexion Medical, Inc. | Radiation therapy systems and methods with tumor tracking |
EP3651851B1 (en) | 2017-07-11 | 2023-11-08 | RefleXion Medical, Inc. | Methods for pet detector afterglow management |
EP3664712A4 (en) * | 2017-08-09 | 2021-05-05 | RefleXion Medical, Inc. | Systems and methods for fault detection in emission-guided radiotherapy |
JP6932253B2 (en) | 2017-09-21 | 2021-09-08 | コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. | Relaxed repetitive maximum likelihood expectation maximization for contingent simultaneous estimation of positron emission tomography |
US11175418B2 (en) * | 2017-09-22 | 2021-11-16 | Koninklijke Philips N.V. | Handling detector pixel performance variation in digital positron emission tomography |
WO2019099551A1 (en) | 2017-11-14 | 2019-05-23 | Reflexion Medical, Inc. | Systems and methods for patient monitoring for radiotherapy |
CN108287361B (en) * | 2018-01-03 | 2019-08-27 | 东软医疗系统股份有限公司 | A kind of detection method and device in single event dead time |
WO2019145398A1 (en) * | 2018-01-26 | 2019-08-01 | Koninklijke Philips N.V. | A dead-time correction method in quantitative positron emission tomography (pet) reconstruction for various objects and radioactivity distributions |
CN111684493A (en) | 2018-01-30 | 2020-09-18 | 皇家飞利浦有限公司 | Correction method for quantization accuracy improvement in list mode reconstruction |
CN108831546A (en) * | 2018-06-22 | 2018-11-16 | 上海联影医疗科技有限公司 | A kind of data processing method, device and non-transient computer readable storage medium |
US10945685B2 (en) * | 2018-07-25 | 2021-03-16 | New York University | System and method for normalizing standardized uptake values in brain positron emission tomography (PET) images |
CN110215227B (en) * | 2019-06-05 | 2022-10-14 | 上海联影医疗科技股份有限公司 | Time window setting method and device, computer equipment and storage medium |
US11002867B1 (en) * | 2019-10-23 | 2021-05-11 | Siemens Medical Solutions Usa, Inc. | Determination of crystal singles rates to estimate mean random coincidence rate |
CN113116371B (en) * | 2019-12-30 | 2024-04-19 | 佳能医疗系统株式会社 | PET device and calibration method |
US11241211B2 (en) * | 2020-03-12 | 2022-02-08 | Canon Medical Systems Corporation | Method and apparatus for singles spectrum estimation and for dead-time correction in positron emission tomography (PET) |
CN111447426B (en) * | 2020-05-13 | 2021-12-31 | 中测新图(北京)遥感技术有限责任公司 | Image color correction method and device |
CN111839566B (en) * | 2020-08-21 | 2023-06-16 | 上海联影医疗科技股份有限公司 | Dead time correction method, system and device for PET imaging equipment and storage medium |
CN112817035B (en) * | 2021-01-28 | 2022-11-25 | 上海联影医疗科技股份有限公司 | Data compensation method and device, computer equipment and storage medium |
CN113359178B (en) * | 2021-03-29 | 2023-05-16 | 山西中辐核仪器有限责任公司 | Radiometer based on self-adaptive dead time compensation |
CN113109225B (en) * | 2021-04-19 | 2023-07-18 | 中国科学院合肥物质科学研究院 | Dead time correction method in CPC particle counter |
EP4242696A1 (en) * | 2022-03-10 | 2023-09-13 | Positrigo AG | Method for determining relative detector element efficiencies in a pet-scanning device |
EP4350396A1 (en) * | 2022-10-05 | 2024-04-10 | Canon Medical Systems Corporation | Pet apparatus, data processing method and program |
Family Cites Families (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5241181A (en) * | 1992-07-27 | 1993-08-31 | General Electric Company | Coincidence detector for a PET scanner |
US6403960B1 (en) | 1999-04-29 | 2002-06-11 | Koninklijijke Philips Electronics N.V. | Correction for spatial variations of deadtime of a monolithic scintillator based detector in a medical imaging system |
US6980683B2 (en) * | 2000-08-28 | 2005-12-27 | Cti Pet Systems, Inc. | On-line correction of patient motion in three-dimensional positron emission tomography |
US7634061B1 (en) * | 2004-03-26 | 2009-12-15 | Nova R & D, Inc. | High resolution imaging system |
US7132663B2 (en) * | 2004-11-04 | 2006-11-07 | General Electric Company | Methods and apparatus for real-time error correction |
US8022368B2 (en) * | 2007-09-17 | 2011-09-20 | Siemens Medical Solutions Usa, Inc. | Hybrid method for randoms variance reduction |
US8359345B2 (en) * | 2008-05-09 | 2013-01-22 | Siemens Medical Solutions Usa, Inc. | Iterative algorithms for variance reduction on compressed sinogram random coincidences in PET |
CN103596502B (en) * | 2011-04-05 | 2016-02-24 | 皇家飞利浦有限公司 | For the adaptive calibration of tomographic imaging system |
US9268046B2 (en) * | 2011-07-12 | 2016-02-23 | Koninklijke Philips N.V. | Imaging system detector calibration |
AU2012292250A1 (en) | 2011-07-20 | 2014-01-23 | Dectris Ltd. | Photon counting imaging method and device with instant retrigger capability |
-
2015
- 2015-12-14 EP EP15816536.5A patent/EP3234647B1/en active Active
- 2015-12-14 WO PCT/IB2015/059594 patent/WO2016097977A1/en active Application Filing
- 2015-12-14 JP JP2017531475A patent/JP6464269B2/en not_active Expired - Fee Related
- 2015-12-14 CN CN201580068529.XA patent/CN107110983B/en not_active Expired - Fee Related
- 2015-12-14 US US15/535,426 patent/US10101474B2/en active Active
Non-Patent Citations (1)
Title |
---|
None * |
Also Published As
Publication number | Publication date |
---|---|
JP2018506706A (en) | 2018-03-08 |
CN107110983B (en) | 2020-02-07 |
US10101474B2 (en) | 2018-10-16 |
CN107110983A (en) | 2017-08-29 |
US20170371046A1 (en) | 2017-12-28 |
EP3234647A1 (en) | 2017-10-25 |
JP6464269B2 (en) | 2019-02-06 |
WO2016097977A1 (en) | 2016-06-23 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
EP3234647B1 (en) | Pixel based dead time correction | |
US10914851B2 (en) | Time of flight calibration in digital positron emission tomography | |
EP2867701B1 (en) | Digital positron emission tomography (dpet) energy calibration method | |
US9226716B2 (en) | Nuclear medicine imaging apparatus and radiation therapy apparatus | |
EP3213119B1 (en) | Pet detector timing calibration | |
US9747701B2 (en) | Systems and methods for emission tomography quantitation | |
RU2582887C2 (en) | Pet calibration with variable match intervals | |
US10215864B2 (en) | System and method to improve image quality of emission tomography when using advanced radionuclides | |
US20110142367A1 (en) | Methods and systems for correcting image scatter | |
US10482634B2 (en) | Systems and methods for imaging with anisotropic voxels | |
US11002867B1 (en) | Determination of crystal singles rates to estimate mean random coincidence rate | |
US9739894B2 (en) | Gamma camera dead time compensation using a companion radioisotope | |
EP3104196B1 (en) | Gamma camera dead time compensation using a companion radioisotope | |
JP2011002306A (en) | Iterative image reconstruction method for pet system | |
Goertzen et al. | A method for measuring the energy spectrum of coincidence events in positron emission tomography | |
Belcari et al. | PET/CT and PET/MR Tomographs: Image Acquisition and Processing | |
US20220343566A1 (en) | Methods and systems for reconstructing a positron emission tomography image |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE |
|
PUAI | Public reference made under article 153(3) epc to a published international application that has entered the european phase |
Free format text: ORIGINAL CODE: 0009012 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE |
|
17P | Request for examination filed |
Effective date: 20170717 |
|
AK | Designated contracting states |
Kind code of ref document: A1 Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR |
|
AX | Request for extension of the european patent |
Extension state: BA ME |
|
DAV | Request for validation of the european patent (deleted) | ||
DAX | Request for extension of the european patent (deleted) | ||
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: EXAMINATION IS IN PROGRESS |
|
17Q | First examination report despatched |
Effective date: 20200107 |
|
RAP1 | Party data changed (applicant data changed or rights of an application transferred) |
Owner name: KONINKLIJKE PHILIPS N.V. |
|
GRAP | Despatch of communication of intention to grant a patent |
Free format text: ORIGINAL CODE: EPIDOSNIGR1 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: GRANT OF PATENT IS INTENDED |
|
INTG | Intention to grant announced |
Effective date: 20200922 |
|
RIN1 | Information on inventor provided before grant (corrected) |
Inventor name: LAURENCE, THOMAS LEROY Inventor name: WANG, SHARON XIAORONG |
|
GRAS | Grant fee paid |
Free format text: ORIGINAL CODE: EPIDOSNIGR3 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: GRANT OF PATENT IS INTENDED |
|
GRAA | (expected) grant |
Free format text: ORIGINAL CODE: 0009210 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE PATENT HAS BEEN GRANTED |
|
AK | Designated contracting states |
Kind code of ref document: B1 Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR |
|
REG | Reference to a national code |
Ref country code: GB Ref legal event code: FG4D |
|
REG | Reference to a national code |
Ref country code: AT Ref legal event code: REF Ref document number: 1367814 Country of ref document: AT Kind code of ref document: T Effective date: 20210315 Ref country code: CH Ref legal event code: EP |
|
REG | Reference to a national code |
Ref country code: DE Ref legal event code: R096 Ref document number: 602015066407 Country of ref document: DE |
|
REG | Reference to a national code |
Ref country code: IE Ref legal event code: FG4D |
|
REG | Reference to a national code |
Ref country code: LT Ref legal event code: MG9D |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: BG Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210603 Ref country code: FI Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: HR Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: GR Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210604 Ref country code: LT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: NO Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210603 |
|
REG | Reference to a national code |
Ref country code: NL Ref legal event code: MP Effective date: 20210303 |
|
REG | Reference to a national code |
Ref country code: AT Ref legal event code: MK05 Ref document number: 1367814 Country of ref document: AT Kind code of ref document: T Effective date: 20210303 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: SE Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: LV Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: RS Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: PL Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: NL Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: SM Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: AT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: CZ Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: EE Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: IS Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210703 Ref country code: PT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210705 Ref country code: SK Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: RO Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |
|
REG | Reference to a national code |
Ref country code: DE Ref legal event code: R097 Ref document number: 602015066407 Country of ref document: DE |
|
PLBE | No opposition filed within time limit |
Free format text: ORIGINAL CODE: 0009261 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: NO OPPOSITION FILED WITHIN TIME LIMIT |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: AL Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: ES Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 Ref country code: DK Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |
|
PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: GB Payment date: 20211221 Year of fee payment: 7 |
|
26N | No opposition filed |
Effective date: 20211206 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: SI Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: IT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: IS Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210703 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: MC Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |
|
REG | Reference to a national code |
Ref country code: CH Ref legal event code: PL |
|
REG | Reference to a national code |
Ref country code: BE Ref legal event code: MM Effective date: 20211231 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: LU Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20211214 Ref country code: IE Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20211214 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: FR Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20211231 Ref country code: BE Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20211231 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: LI Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20211231 Ref country code: CH Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20211231 |
|
PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: DE Payment date: 20220628 Year of fee payment: 8 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: HU Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT; INVALID AB INITIO Effective date: 20151214 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: CY Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |
|
GBPC | Gb: european patent ceased through non-payment of renewal fee |
Effective date: 20221214 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: GB Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20221214 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: MK Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20210303 |